Software requirements specification (SRS) is an essential part of software development. SRS has two features: functional requirements (FR) and non-functional requirements (NFR). Functional requirements define the needs that are directly in contact with stakeholders. Non-functional requirements describe how the software provides the means to carry out functional requirements. Non-functional requirements are often mixed with functional requirements. This study compares four primarily used machine learning methods for classifying functional and non-functional requirements. The contribution of our research is to use the PROMISE and SecReq (ePurse) dataset, then classify them by comparing the FastText+SVM, FastText+CNN, SVM, and CNN classification methods. CNN outperformed other methods on both datasets. The accuracy obtained by CNN on the PROMISE dataset is 99% and on the Seqreq dataset is 94%.
CITATION STYLE
Baskoro, F., Andrahsmara, R. A., Darnoto, B. R. P., & Tofan, Y. A. (2021). A Systematic Comparison of Software Requirements Classification. IPTEK The Journal for Technology and Science, 32(3), 184. https://doi.org/10.12962/j20882033.v32i3.13005
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